Innovation, as a source of competitive advantage, has never been more critical or complex. Meanwhile, rapid advances in artificial intelligence (AI) are reshaping how organizations generate ideas, make decisions, design work, and create value. Yet technology alone does not produce innovation, and that is true in the age of AI. Leaders must also build the organizational systems, cultures, and capabilities that turn promising ideas into meaningful impact.

Innovation in the Age of AI is an immersive four-day program designed to help leaders approach innovation strategically in a period of accelerating change. Drawing on MIT research and practice across innovation, entrepreneurship, leadership, organizational design, and artificial intelligence, the course examines how organizations can innovate repeatedly, effectively, and at scale.

Participants will explore both “Big I” Innovation—the transformative initiatives and emerging technologies that can create significant new value—and “little i” innovation—the everyday practices, experiments, and improvements that make an organization more adaptive. Through faculty-led sessions, collaborative exercises, practical assessments, and engagement with the Kendall Square innovation ecosystem, participants will develop a more integrated approach to leading innovation in the age of AI.

At the end of this course, you will be able to:

• Apply a systems-level framework for moving ideas from inception to impact.
• Assess your organization’s current innovation practices and identify where innovation thrives or stalls.
• Balance breakthrough “Big I” initiatives with the everyday “little i” practices that support continuous improvement.
• Evaluate how generative AI can accelerate inquiry, experimentation, decision-making, and value creation.
• Identify opportunities to integrate AI into innovation processes while preserving human judgment and trust.
• Develop an innovation portfolio that balances near-term opportunities with longer-term strategic initiatives.
• Engage external ecosystems—including start-ups, universities, investors, governments, and corporate partners—to expand innovation capacity.
• Create organizational conditions that support experimentation, collaboration, agility, and learning.
• Lead teams and stakeholders through uncertainty, complexity, and change.
• Translate course insights into a focused plan for advancing innovation within your organization.

This course combines research-based frameworks with immersive, hands-on learning. Participants will examine innovation through multiple, interconnected lenses: organizational systems and ecosystems, AI-enabled innovation, leadership and culture, team effectiveness, and the design of work.

Central to the experience is an MIT Sloan research-based framework for assessing an organization’s innovation practices. Participants will identify where ideas are able to advance, where innovation tends to stall, and which structural or leadership interventions can improve results. An accompanying innovation handbook will help participants apply course concepts to their own organizations and shape a practical path forward.

The program also extends beyond the classroom into the Kendall Square innovation ecosystem, including an experience at the Venture Café gathering. This engagement gives participants an opportunity to observe how entrepreneurs, researchers, investors, corporations, and other stakeholders connect to exchange knowledge and accelerate innovation.

Across the four days, participants will consider how generative AI can strengthen inquiry, experimentation, decision-making, and innovation processes. The course emphasizes a human-centered approach in which AI creates the greatest value when combined with curiosity, judgment, trust, and strong organizational capabilities.

Day One: AI is Accelerating, Including Innovation

Central Questions: How is generative AI changing the way organizations operate, and innovate? Where can AI strengthen inquiry, experimentation, decision-making, and value creation?

Participants explore the foundations and organizational implications of generative AI. Sessions examine AI-accelerated inquiry, the role of better questions in innovation, approaches to building sustainable AI capabilities, and the importance of trust and human judgment in AI-enabled systems.

Day Two: Building your Organization’s Innovation System

Central Questions: How do organizations move ideas from inception to impact? What internal systems and external relationships allow innovation to flourish?

Participants examine innovation pipelines, portfolios, and external ecosystems to assess how their organizations currently support—or inhibit—innovation. They consider how corporations can engage start-ups, universities, investors, governments, and other ecosystem stakeholders to accelerate learning and growth.

Day Three: Leading Innovative Organizations

Central Questions: What leadership behaviors and team practices enable innovation? How can leaders mobilize people and sustain momentum through complexity and change?

Participants explore distributed and collaborative leadership, stakeholder alignment, and the dynamics of high-performing teams. Interactive learning experiences illuminate how communication, organizational conditions, and leadership choices influence a team’s ability to experiment, adapt, and execute.

Day Four: Designing the Organization—and the Path—Forward

Central Questions: How can organizations design work for adaptability and continuous improvement? How will participants apply their learning to advance innovation after the course?

Participants examine how roles, structures, management systems, and work practices can enable—or constrain—innovation. Drawing together lessons from the classroom and the Kendall Square ecosystem, they articulate priorities and develop a practical plan for strengthening innovation in their organizations.